Intercellular Communication Guides the Prediction of Intracellular Gene Regulatory Relationships.

Journal: Journal of chemical information and modeling
Published Date: Jan 6, 2026

Abstract

Cellular communication via ligand-receptor signaling regulates downstream gene expression networks, playing a vital role in maintaining cellular functions and driving disease progression. However, the current methods do not account for the synergistic interactions between cellular communication and downstream gene regulatory networks. Moreover, existing approaches cannot construct complete cellular communication networks, thereby limiting biological significance and interpretability. To address these gaps, we propose a computational framework that predicts intracellular gene regulatory relationships by constructing comprehensive cellular communication networks. The framework introduces two key innovations: (1) end-to-end modeling from extracellular signals to gene expression by integrating ligand-receptor interactions, signaling pathway activation, and transcription factor regulatory networks and (2) accurate modeling of receptor-mediated regulatory relationships using deep learning to reveal intracellular mechanisms driven by cellular communication. Experimental results and case studies show that the framework efficiently predicts receptor-mediated target gene regulatory relationships across diverse spatial transcriptomic data sets and provides a valuable tool for uncovering biological processes.

Authors

  • Zhecheng Zhou
    Wenzhou University of Technology, 325000 Wenzhou, China.
  • Zhen Li
    PepsiCo R&D, Valhalla, NY, United States.
  • Yunfei Xie
    Key Laboratory for Micro-Nano Physics and Technology of Hunan Province, Hunan Institute of Optoelectronic Integration, College of Materials Science and Engineering, Hunan University, Changsha, Hunan, 410082, P. R. China.
  • Linlin Zhuo
    School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou, Zhejiang 325035, China; College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
  • Rui Wang
    Department of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People's Hospital, Hohhot, Inner Mongolia, China.
  • Xiaojun Yao
    Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao, 999078, PR China.
  • Haiyang Hu
    Department of Cardiology and Critical Care Medicine, Affiliated Hospital of Jining Medical College, Jining, China.
  • Xiangzheng Fu

Keywords

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